topic "Painter";
[i448;a25;kKO9;2 $$1,0#37138531426314131252341829483380:class]
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[{_} 
[ {{10000@(113.42.0) [s0;%% [*@7;4 Painter]]}}&]
[s0; &]
[s0; Painter is an abstract class that represents `"SVG level`" rendering 
engine, supporting cubic and quadratic Bezier paths, affine transformations, 
filling and stroking with raster images, linear or radial gradients, 
clipping and alpha masking.&]
[s0; &]
[s0; &]
[ {{10000F(128)G(128)@1 [s0;%% [* Path definition methods]]}}&]
[s3; &]
[s5;:Upp`:`:Painter`:`:Move`(const Upp`:`:Pointf`&`,bool`): Painter[@(0.0.255) `&] 
[* Move]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p], [@(0.0.255) bool] 
[*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Move`(const Upp`:`:Pointf`&`): Painter[@(0.0.255) `&] 
[* Move]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:Move`(double`,double`,bool`): Painter[@(0.0.255) `&] 
[* Move]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], [@(0.0.255) bool] 
[*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Move`(double`,double`): Painter[@(0.0.255) `&] 
[* Move]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:RelMove`(const Upp`:`:Pointf`&`): Painter[@(0.0.255) `&] 
[* RelMove]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:RelMove`(double`,double`): Painter[@(0.0.255) `&] 
[* RelMove]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s2;%% Move to a new path point, without any visual connection to 
the previous path. Path definition usually starts with Move. 
[%-*@3 p] or [%-*@3 x], [%-*@3 y] specify the point, if [%-*@3 rel] is 
true or with [* RelMove] the position is relative to the last point 
of path.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Line`(const Upp`:`:Pointf`&`,bool`): Painter[@(0.0.255) `&] 
[* Line]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p], [@(0.0.255) bool] 
[*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Line`(const Upp`:`:Pointf`&`): Painter[@(0.0.255) `&] 
[* Line]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:Line`(double`,double`,bool`): Painter[@(0.0.255) `&] 
[* Line]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], [@(0.0.255) bool] 
[*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Line`(double`,double`): Painter[@(0.0.255) `&] 
[* Line]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:RelLine`(const Upp`:`:Pointf`&`): Painter[@(0.0.255) `&] 
[* RelLine]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:RelLine`(double`,double`): Painter[@(0.0.255) `&] 
[* RelLine]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s2;%% Add a line to the current path from the last point of path 
to [%-*@3 p] / [%-*@3 x] [%-*@3 y]. If [%-*@3 rel] is true or with [* RelLine] 
the position is relative to the last point of path.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Quadratic`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,bool`): P
ainter[@(0.0.255) `&] [* Quadratic]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p1], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p], [@(0.0.255) bool] 
[*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Quadratic`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`): Pai
nter[@(0.0.255) `&] [* Quadratic]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p1], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:Quadratic`(const Upp`:`:Pointf`&`): Painter[@(0.0.255) `&] 
[* Quadratic]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:Quadratic`(double`,double`,bool`): Painter[@(0.0.255) `&] 
[* Quadratic]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], 
[@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Quadratic`(double`,double`,double`,double`,bool`): Painter[@(0.0.255) `&
] [* Quadratic]([@(0.0.255) double] [*@3 x1], [@(0.0.255) double] [*@3 y1], 
[@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], [@(0.0.255) bool] 
[*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Quadratic`(const Upp`:`:Pointf`&`,bool`): Painter[@(0.0.255) `&] 
[* Quadratic]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p], [@(0.0.255) bool] 
[*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Quadratic`(double`,double`,double`,double`): Painter[@(0.0.255) `&
] [* Quadratic]([@(0.0.255) double] [*@3 x1], [@(0.0.255) double] [*@3 y1], 
[@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:Quadratic`(double`,double`): Painter[@(0.0.255) `&] 
[* Quadratic]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:RelQuadratic`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`): P
ainter[@(0.0.255) `&] [* RelQuadratic]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p1], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:RelQuadratic`(double`,double`,double`,double`): Painter[@(0.0.255) `&
] [* RelQuadratic]([@(0.0.255) double] [*@3 x1], [@(0.0.255) double] 
[*@3 y1], [@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:RelQuadratic`(double`,double`): Painter[@(0.0.255) `&] 
[* RelQuadratic]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:RelQuadratic`(const Upp`:`:Pointf`&`): Painter[@(0.0.255) `&] 
[* RelQuadratic]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s2;%% Adds quadratic Bezier curve to final point [%-*@3 p ][%- /][%-*@3  
x] [%-*@3 y ][%- with control point][%-*@3  p1] / [%-*@3 x1] [%-*@3 y1]. 
If [%-*@3 rel] is true or with [* RelQuadratic] the points are relative 
to the last point of path.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Cubic`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,bool`): P
ainter[@(0.0.255) `&] [* Cubic]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p1], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p2], [@(0.0.255) const] 
Pointf[@(0.0.255) `&] [*@3 p], [@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Cubic`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,bool`): P
ainter[@(0.0.255) `&] [* Cubic]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p2], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p], [@(0.0.255) bool] 
[*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Cubic`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`): P
ainter[@(0.0.255) `&] [* Cubic]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p1], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p2], [@(0.0.255) const] 
Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:Cubic`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`): Painter
[@(0.0.255) `&] [* Cubic]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p2], 
[@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:Cubic`(double`,double`,double`,double`,double`,double`,bool`): P
ainter[@(0.0.255) `&] [* Cubic]([@(0.0.255) double] [*@3 x1], [@(0.0.255) double] 
[*@3 y1], [@(0.0.255) double] [*@3 x2], [@(0.0.255) double] [*@3 y2], [@(0.0.255) double] 
[*@3 x], [@(0.0.255) double] [*@3 y], [@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Cubic`(double`,double`,double`,double`,bool`): Painter[@(0.0.255) `&
] [* Cubic]([@(0.0.255) double] [*@3 x2], [@(0.0.255) double] [*@3 y2], 
[@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], [@(0.0.255) bool] 
[*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Cubic`(double`,double`,double`,double`,double`,double`): Paint
er[@(0.0.255) `&] [* Cubic]([@(0.0.255) double] [*@3 x1], [@(0.0.255) double] 
[*@3 y1], [@(0.0.255) double] [*@3 x2], [@(0.0.255) double] [*@3 y2], [@(0.0.255) double] 
[*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:Cubic`(double`,double`,double`,double`): Painter[@(0.0.255) `&] 
[* Cubic]([@(0.0.255) double] [*@3 x2], [@(0.0.255) double] [*@3 y2], [@(0.0.255) double] 
[*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:RelCubic`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`): P
ainter[@(0.0.255) `&] [* RelCubic]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p1], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p2], [@(0.0.255) const] 
Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:RelCubic`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`): Pain
ter[@(0.0.255) `&] [* RelCubic]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p2], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:RelCubic`(double`,double`,double`,double`,double`,double`): Pa
inter[@(0.0.255) `&] [* RelCubic]([@(0.0.255) double] [*@3 x1], [@(0.0.255) double] 
[*@3 y1], [@(0.0.255) double] [*@3 x2], [@(0.0.255) double] [*@3 y2], [@(0.0.255) double] 
[*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:RelCubic`(double`,double`,double`,double`): Painter[@(0.0.255) `&
] [* RelCubic]([@(0.0.255) double] [*@3 x2], [@(0.0.255) double] [*@3 y2], 
[@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s2;%% Adds cubic Bezier curve to final point [%-*@3 p ][%- /][%-*@3  x] 
[%-*@3 y ][%- with control points][%-*@3  p1] / [%-*@3 x1] [%-*@3 y1].and 
[%-*@3 p2] / [%-*@3 x2] [%-*@3 y2]. If [%-*@3 rel] is true or with [* RelCubic] 
the points are relative to the last point of path.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Arc`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,double`,double`,bool`): P
ainter[@(0.0.255) `&] [* Arc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 c], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 r], [@(0.0.255) double] 
[*@3 angle], [@(0.0.255) double] [*@3 sweep], [@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Arc`(const Upp`:`:Pointf`&`,double`,double`,double`,double`,bool`): P
ainter[@(0.0.255) `&] [* Arc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 c], [@(0.0.255) double] [*@3 rx], [@(0.0.255) double] [*@3 ry], [@(0.0.255) double] 
[*@3 angle], [@(0.0.255) double] [*@3 sweep], [@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Arc`(const Upp`:`:Pointf`&`,double`,double`,double`,bool`): Pa
inter[@(0.0.255) `&] [* Arc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 c], [@(0.0.255) double] [*@3 r], [@(0.0.255) double] [*@3 angle], 
[@(0.0.255) double] [*@3 sweep], [@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Arc`(double`,double`,double`,double`,double`,double`,bool`): P
ainter[@(0.0.255) `&] [* Arc]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y], [@(0.0.255) double] [*@3 rx], [@(0.0.255) double] [*@3 ry], [@(0.0.255) double] 
[*@3 angle], [@(0.0.255) double] [*@3 sweep], [@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Arc`(double`,double`,double`,double`,double`,bool`): Painter[@(0.0.255) `&
] [* Arc]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], [@(0.0.255) double] 
[*@3 r], [@(0.0.255) double] [*@3 angle], [@(0.0.255) double] [*@3 sweep], 
[@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:Arc`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,double`,double`): P
ainter[@(0.0.255) `&] [* Arc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 c], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 r], [@(0.0.255) double] 
[*@3 angle], [@(0.0.255) double] [*@3 sweep])&]
[s5;:Upp`:`:Painter`:`:Arc`(const Upp`:`:Pointf`&`,double`,double`,double`,double`): P
ainter[@(0.0.255) `&] [* Arc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 c], [@(0.0.255) double] [*@3 rx], [@(0.0.255) double] [*@3 ry], [@(0.0.255) double] 
[*@3 angle], [@(0.0.255) double] [*@3 sweep])&]
[s5;:Upp`:`:Painter`:`:Arc`(const Upp`:`:Pointf`&`,double`,double`,double`): Painter[@(0.0.255) `&
] [* Arc]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 c], [@(0.0.255) double] 
[*@3 r], [@(0.0.255) double] [*@3 angle], [@(0.0.255) double] [*@3 sweep])&]
[s5;:Upp`:`:Painter`:`:Arc`(double`,double`,double`,double`,double`,double`): Painter
[@(0.0.255) `&] [* Arc]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y], [@(0.0.255) double] [*@3 rx], [@(0.0.255) double] [*@3 ry], [@(0.0.255) double] 
[*@3 angle], [@(0.0.255) double] [*@3 sweep])&]
[s5;:Upp`:`:Painter`:`:Arc`(double`,double`,double`,double`,double`): Painter[@(0.0.255) `&
] [* Arc]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], [@(0.0.255) double] 
[*@3 r], [@(0.0.255) double] [*@3 angle], [@(0.0.255) double] [*@3 sweep])&]
[s5;:Upp`:`:Painter`:`:RelArc`(const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,double`,double`): P
ainter[@(0.0.255) `&] [* RelArc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 c], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 r], [@(0.0.255) double] 
[*@3 angle], [@(0.0.255) double] [*@3 sweep])&]
[s5;:Upp`:`:Painter`:`:RelArc`(const Upp`:`:Pointf`&`,double`,double`,double`,double`): P
ainter[@(0.0.255) `&] [* RelArc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 c], [@(0.0.255) double] [*@3 rx], [@(0.0.255) double] [*@3 ry], [@(0.0.255) double] 
[*@3 angle], [@(0.0.255) double] [*@3 sweep])&]
[s5;:Upp`:`:Painter`:`:RelArc`(const Upp`:`:Pointf`&`,double`,double`,double`): Paint
er[@(0.0.255) `&] [* RelArc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 c], [@(0.0.255) double] [*@3 r], [@(0.0.255) double] [*@3 angle], 
[@(0.0.255) double] [*@3 sweep])&]
[s5;:Upp`:`:Painter`:`:RelArc`(double`,double`,double`,double`,double`,double`): Pain
ter[@(0.0.255) `&] [* RelArc]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y], [@(0.0.255) double] [*@3 rx], [@(0.0.255) double] [*@3 ry], [@(0.0.255) double] 
[*@3 angle], [@(0.0.255) double] [*@3 sweep])&]
[s5;:Upp`:`:Painter`:`:RelArc`(double`,double`,double`,double`,double`): Painter[@(0.0.255) `&
] [* RelArc]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], 
[@(0.0.255) double] [*@3 r], [@(0.0.255) double] [*@3 angle], [@(0.0.255) double] 
[*@3 sweep])&]
[s2;%% Adds circular or elliptical arc. [%-*@3 c] / [%-*@3 x] [%-*@3 y] 
is the center of circle or ellipse, [%-*@3 r] is the radius of 
circle if it is double or horizontal and vertical radius specified 
as Pointf, [%-*@3 rx] [%-*@3 ry] are ellipse radii, [%-*@3 angle] is 
the starting angle of arc in radians where 0 is the angle of 
positive x axis, [%-*@3 sweep] is the ending angle of arc, positive 
sweep is in clockwise direction. The line is first added from 
the current position to the starting point of arc (if you want 
arc without it, just Move the position to the starting point). 
If [%-*@3 rel] is true or with [%-* RelArc ]the center is relative 
to the last point of path.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:SvgArc`(const Upp`:`:Pointf`&`,double`,bool`,bool`,const Upp`:`:Pointf`&`,bool`): P
ainter[@(0.0.255) `&] [* SvgArc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 r], [@(0.0.255) double] [*@3 xangle], [@(0.0.255) bool] [*@3 large], 
[@(0.0.255) bool] [*@3 sweep], [@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p], [@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:SvgArc`(double`,double`,double`,bool`,bool`,const Upp`:`:Pointf`&`,bool`): P
ainter[@(0.0.255) `&] [* SvgArc]([@(0.0.255) double] [*@3 rx], [@(0.0.255) double] 
[*@3 ry], [@(0.0.255) double] [*@3 xangle], [@(0.0.255) bool] [*@3 large], 
[@(0.0.255) bool] [*@3 sweep], [@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p], [@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:SvgArc`(double`,double`,double`,bool`,bool`,double`,double`,bool`): P
ainter[@(0.0.255) `&] [* SvgArc]([@(0.0.255) double] [*@3 rx], [@(0.0.255) double] 
[*@3 ry], [@(0.0.255) double] [*@3 xangle], [@(0.0.255) bool] [*@3 large], 
[@(0.0.255) bool] [*@3 sweep], [@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y], [@(0.0.255) bool] [*@3 rel])&]
[s5;:Upp`:`:Painter`:`:SvgArc`(const Upp`:`:Pointf`&`,double`,bool`,bool`,const Upp`:`:Pointf`&`): P
ainter[@(0.0.255) `&] [* SvgArc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 r], [@(0.0.255) double] [*@3 xangle], [@(0.0.255) bool] [*@3 large], 
[@(0.0.255) bool] [*@3 sweep], [@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p])&]
[s5;:Upp`:`:Painter`:`:SvgArc`(double`,double`,double`,bool`,bool`,const Upp`:`:Pointf`&`): P
ainter[@(0.0.255) `&] [* SvgArc]([@(0.0.255) double] [*@3 rx], [@(0.0.255) double] 
[*@3 ry], [@(0.0.255) double] [*@3 xangle], [@(0.0.255) bool] [*@3 large], 
[@(0.0.255) bool] [*@3 sweep], [@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p])&]
[s5;:Upp`:`:Painter`:`:SvgArc`(double`,double`,double`,bool`,bool`,double`,double`): P
ainter[@(0.0.255) `&] [* SvgArc]([@(0.0.255) double] [*@3 rx], [@(0.0.255) double] 
[*@3 ry], [@(0.0.255) double] [*@3 xangle], [@(0.0.255) bool] [*@3 large], 
[@(0.0.255) bool] [*@3 sweep], [@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y])&]
[s5;:Upp`:`:Painter`:`:RelSvgArc`(const Upp`:`:Pointf`&`,double`,bool`,bool`,const Upp`:`:Pointf`&`): P
ainter[@(0.0.255) `&] [* RelSvgArc]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 r], [@(0.0.255) double] [*@3 xangle], [@(0.0.255) bool] [*@3 large], 
[@(0.0.255) bool] [*@3 sweep], [@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p])&]
[s5;:Upp`:`:Painter`:`:RelSvgArc`(double`,double`,double`,bool`,bool`,const Upp`:`:Pointf`&`): P
ainter[@(0.0.255) `&] [* RelSvgArc]([@(0.0.255) double] [*@3 rx], [@(0.0.255) double] 
[*@3 ry], [@(0.0.255) double] [*@3 xangle], [@(0.0.255) bool] [*@3 large], 
[@(0.0.255) bool] [*@3 sweep], [@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p])&]
[s5;:Upp`:`:Painter`:`:RelSvgArc`(double`,double`,double`,bool`,bool`,double`,double`): P
ainter[@(0.0.255) `&] [* RelSvgArc]([@(0.0.255) double] [*@3 rx], [@(0.0.255) double] 
[*@3 ry], [@(0.0.255) double] [*@3 xangle], [@(0.0.255) bool] [*@3 large], 
[@(0.0.255) bool] [*@3 sweep], [@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y])&]
[s2;%% Adds arc specified by SVG compatible definition. If [%-*@3 rel] 
is true or with [%-* RelSvgArc ]the center is relative to the last 
point of path.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Path`(Upp`:`:CParser`&`): Painter[@(0.0.255) `&] 
[* Path](CParser[@(0.0.255) `&] [*@3 p])&]
[s5;:Upp`:`:Painter`:`:Path`(const char`*`): Painter[@(0.0.255) `&] 
[* Path]([@(0.0.255) const] [@(0.0.255) char] [@(0.0.255) `*][*@3 path])&]
[s2;%% Adds path by parsing input text in SVG path definition format.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Character`(const Upp`:`:Pointf`&`,int`,Upp`:`:Font`): Painter[@(0.0.255) `&
] [* Character]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p], [@(0.0.255) int] 
[*@3 ch], Font [*@3 fnt])&]
[s5;:Upp`:`:Painter`:`:Character`(double`,double`,int`,Upp`:`:Font`): Painter[@(0.0.255) `&
] [* Character]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], 
[@(0.0.255) int] [*@3 ch], Font [*@3 fnt])&]
[s2;%% [%- Adds character with UNICODE codepoint ][%-*@3 ch] from Font 
[%-*@3 fnt ](font can be replaced if given character is missing 
in it) at the position[%-*@3  p] / [%-*@3 x] [%-*@3 y].&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Text`(const Upp`:`:Pointf`&`,const Upp`:`:wchar`*`,Upp`:`:Font`,int`,const double`*`): P
ainter[@(0.0.255) `&] [* Text]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p], [@(0.0.255) const] wchar [@(0.0.255) `*][*@3 text], Font [*@3 fnt], 
[@(0.0.255) int] [*@3 n] [@(0.0.255) `=] [@(0.0.255) `-][@3 1], [@(0.0.255) const] 
[@(0.0.255) double] [@(0.0.255) `*][*@3 dx] [@(0.0.255) `=] [@3 0])&]
[s5;:Upp`:`:Painter`:`:Text`(double`,double`,const Upp`:`:wchar`*`,Upp`:`:Font`,int`,const double`*`): P
ainter[@(0.0.255) `&] [* Text]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y], [@(0.0.255) const] wchar [@(0.0.255) `*][*@3 text], Font [*@3 fnt], 
[@(0.0.255) int] [*@3 n] [@(0.0.255) `=] [@(0.0.255) `-][@3 1], [@(0.0.255) const] 
[@(0.0.255) double] [@(0.0.255) `*][*@3 dx] [@(0.0.255) `=] [@3 0])&]
[s5;:Upp`:`:Painter`:`:Text`(const Upp`:`:Pointf`&`,const Upp`:`:WString`&`,Upp`:`:Font`,const double`*`): P
ainter[@(0.0.255) `&] [* Text]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p], [@(0.0.255) const] WString[@(0.0.255) `&] [*@3 s], Font [*@3 fnt], 
[@(0.0.255) const] [@(0.0.255) double] [@(0.0.255) `*][*@3 dx] [@(0.0.255) `=] 
[@3 0])&]
[s5;:Upp`:`:Painter`:`:Text`(double`,double`,const Upp`:`:WString`&`,Upp`:`:Font`,const double`*`): P
ainter[@(0.0.255) `&] [* Text]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y], [@(0.0.255) const] WString[@(0.0.255) `&] [*@3 s], Font [*@3 fnt], 
[@(0.0.255) const] [@(0.0.255) double] [@(0.0.255) `*][*@3 dx] [@(0.0.255) `=] 
[@3 0])&]
[s5;:Upp`:`:Painter`:`:Text`(const Upp`:`:Pointf`&`,const Upp`:`:String`&`,Upp`:`:Font`,const double`*`): P
ainter[@(0.0.255) `&] [* Text]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p], [@(0.0.255) const] String[@(0.0.255) `&] [*@3 s], Font [*@3 fnt], 
[@(0.0.255) const] [@(0.0.255) double] [@(0.0.255) `*][*@3 dx] [@(0.0.255) `=] 
[@3 0])&]
[s5;:Upp`:`:Painter`:`:Text`(double`,double`,const Upp`:`:String`&`,Upp`:`:Font`,const double`*`): P
ainter[@(0.0.255) `&] [* Text]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y], [@(0.0.255) const] String[@(0.0.255) `&] [*@3 s], Font [*@3 fnt], 
[@(0.0.255) const] [@(0.0.255) double] [@(0.0.255) `*][*@3 dx] [@(0.0.255) `=] 
[@3 0])&]
[s5;:Upp`:`:Painter`:`:Text`(const Upp`:`:Pointf`&`,const char`*`,Upp`:`:Font`,int`,const double`*`): P
ainter[@(0.0.255) `&] [* Text]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p], [@(0.0.255) const] [@(0.0.255) char] [@(0.0.255) `*][*@3 text], 
Font [*@3 fnt], [@(0.0.255) int] [*@3 n] [@(0.0.255) `=] [@(0.0.255) `-][@3 1], 
[@(0.0.255) const] [@(0.0.255) double] [@(0.0.255) `*][*@3 dx] [@(0.0.255) `=] 
[@3 0])&]
[s5;:Upp`:`:Painter`:`:Text`(double`,double`,const char`*`,Upp`:`:Font`,int`,const double`*`): P
ainter[@(0.0.255) `&] [* Text]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y], [@(0.0.255) const] [@(0.0.255) char] [@(0.0.255) `*][*@3 text], 
Font [*@3 fnt], [@(0.0.255) int] [*@3 n] [@(0.0.255) `=] [@(0.0.255) `-][@3 1], 
[@(0.0.255) const] [@(0.0.255) double] [@(0.0.255) `*][*@3 dx] [@(0.0.255) `=] 
[@3 0])&]
[s2;%% Convenience method that renders [%-*@3 text] (using Character 
method) at [%-*@3 p] / [%-*@3 x] [%-*@3 y] using [%-*@3 fnt]. Number 
of characters can be limited to [%-*@3 n] (`-1 means render all 
of them, advance between characters can be overriden with [%-*@3 dx].&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Rectangle`(double`,double`,double`,double`): Painter[@(0.0.255) `&
] [* Rectangle]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], 
[@(0.0.255) double] [*@3 cx], [@(0.0.255) double] [*@3 cy])&]
[s5;:Upp`:`:Painter`:`:Rectangle`(const Rectf`&`): Painter[@(0.0.255) `&] 
[* Rectangle]([@(0.0.255) const] Rectf[@(0.0.255) `&] [*@3 r])&]
[s5;:Upp`:`:Painter`:`:Rectangle`(Pointf`,Pointf`): Painter[@(0.0.255) `&] 
[* Rectangle](Pointf [*@3 p1], Pointf [*@3 p2])&]
[s2;%% Convenience method that adds a rectangle to the path.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:RoundedRectangle`(double`,double`,double`,double`,double`): Pa
inter[@(0.0.255) `&] [* RoundedRectangle]([@(0.0.255) double] [*@3 x], 
[@(0.0.255) double] [*@3 y], [@(0.0.255) double] [*@3 cx], [@(0.0.255) double] 
[*@3 cy], [@(0.0.255) double] [*@3 r])&]
[s5;:Upp`:`:Painter`:`:RoundedRectangle`(double`,double`,double`,double`,double`,double`): P
ainter[@(0.0.255) `&] [* RoundedRectangle]([@(0.0.255) double] [*@3 x], 
[@(0.0.255) double] [*@3 y], [@(0.0.255) double] [*@3 cx], [@(0.0.255) double] 
[*@3 cy], [@(0.0.255) double] [*@3 rx], [@(0.0.255) double] [*@3 ry])&]
[s5;:Upp`:`:Painter`:`:RoundedRectangle`(const Rectf`&`,double`): Painter[@(0.0.255) `&
] [* RoundedRectangle]([@(0.0.255) const] Rectf[@(0.0.255) `&] [*@3 rc], 
[@(0.0.255) double] [*@3 r])&]
[s5;:Upp`:`:Painter`:`:RoundedRectangle`(Pointf`,Pointf`,double`): Painter[@(0.0.255) `&
] [* RoundedRectangle](Pointf [*@3 p1], Pointf [*@3 p2], [@(0.0.255) double] 
[*@3 r])&]
[s5;:Upp`:`:Painter`:`:RoundedRectangle`(const Rectf`&`,double`,double`): Painter[@(0.0.255) `&
] [* RoundedRectangle]([@(0.0.255) const] Rectf[@(0.0.255) `&] [*@3 r], 
[@(0.0.255) double] [*@3 r1], [@(0.0.255) double] [*@3 r2])&]
[s5;:Upp`:`:Painter`:`:RoundedRectangle`(Pointf`,Pointf`,double`,double`): Painter[@(0.0.255) `&
] [* RoundedRectangle](Pointf [*@3 p1], Pointf [*@3 p2], [@(0.0.255) double] 
[*@3 r1], [@(0.0.255) double] [*@3 r2])&]
[s2;%% Convenience method that adds rounded rectangle to the path. 
[%-*@3 r] specifies the radius of circular corner, [%-*@3 rx] [%-*@3 ry] 
radii of elliptical corners.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Ellipse`(double`,double`,double`,double`): Painter[@(0.0.255) `&
] [* Ellipse]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], 
[@(0.0.255) double] [*@3 rx], [@(0.0.255) double] [*@3 ry])&]
[s5;:Upp`:`:Painter`:`:Ellipse`(const Rectf`&`): Painter[@(0.0.255) `&] 
[* Ellipse]([@(0.0.255) const] Rectf[@(0.0.255) `&] [*@3 r])&]
[s5;:Upp`:`:Painter`:`:Ellipse`(Pointf`,Pointf`): Painter[@(0.0.255) `&] 
[* Ellipse](Pointf [*@3 p1], Pointf [*@3 p2])&]
[s2;%% Convenience method that adds ellipse to the path.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Circle`(double`,double`,double`): Painter[@(0.0.255) `&] 
[* Circle]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], [@(0.0.255) double] 
[*@3 r])&]
[s5;:Upp`:`:Painter`:`:Circle`(Pointf`,double`): Painter[@(0.0.255) `&] 
[* Circle](Pointf [*@3 p], [@(0.0.255) double] [*@3 r])&]
[s2;%% Convenience method that adds circle to the path.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Div`(`): Painter[@(0.0.255) `&] [* Div]()&]
[s2;%% Divides path into groups that are treated separately with 
respect to current `"insideness`" rule (even`-odd or non`-zero 
winding rule). For example:&]
[s2;%% [C1 sw.Circle(200, 200, 100).Circle(270, 200, 100).EvenOdd().Fill(Black());]&]
[s2;%% 
@@image:457&339
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)
&]
[s2;%% produces shape with `"hole`" where circles overlap, by adding 
Div into path&]
[s2;%% [C1 sw.Circle(200, 200, 100).][*C1 Div()][C1 .Circle(270, 200, 100).EvenOdd().Fill(B
lack());]&]
[s2;%% 
@@image:449&333
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)
&]
[s2;%% circles are treated as separate subshapes and simply overwrite 
each other.&]
[s2;%% This feature is especially important when drawing text with 
effects as it allows individual characters to be grouped to use 
single fill or stroke (glyphs and advance widths are often designed 
with possible overlaps).&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Close`(`): Painter[@(0.0.255) `&] [* Close]()&]
[s2;%% Adds line from the last point of path back to the first point 
(if they are not equal). Note that this is done automatically 
in any Fill call.&]
[s3; &]
[s0; &]
[ {{10000F(128)G(128)@1 [s0;%% [* Filling and Stroking]]}}&]
[s9; [* Fill] is operation that affects all pixels inside the path 
(as defined by current insidness rule). [* Stroke] interprets the 
path as `"line`" with thickness defined as Stroke [*@3 width][%%  
and ]affects pixels in the line. The Stroke line appearance is 
also affected by [* LineCap], [* LineJoin], [* MiterLimit ]and [* Dash] 
attributes. The number of Stroke and Fill operations on single 
path is not limited.&]
[s3; &]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,const Upp`:`:RGBA`&`): Painter[@(0.0.255) `&] 
[* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color])&]
[s5;:Upp`:`:Painter`:`:Fill`(const Upp`:`:RGBA`&`): Painter[@(0.0.255) `&] 
[* Fill]([@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color])&]
[s2;%% [%- Fills or strokes the path with solid ][%-*@3 color].&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Fill`(const Upp`:`:Image`&`,const Upp`:`:Xform2D`&`,Upp`:`:dword`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) const] Image[@(0.0.255) `&] 
[*@3 image], [@(0.0.255) const] Xform2D[@(0.0.255) `&] [*@3 transsrc 
][@(0.0.255) `=] Xform2D[@(0.0.255) `::]Identity(), dword [*@3 flags] 
[@(0.0.255) `=] [@3 0])&]
[s5;:Upp`:`:Painter`:`:Fill`(const Upp`:`:Image`&`,Upp`:`:Pointf`,Upp`:`:Pointf`,Upp`:`:dword`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) const] Image[@(0.0.255) `&] 
[*@3 image], Pointf [*@3 p1], Pointf [*@3 p2], dword [*@3 flags] [@(0.0.255) `=] 
[@3 0])&]
[s5;:Upp`:`:Painter`:`:Fill`(const Upp`:`:Image`&`,double`,double`,double`,double`,Upp`:`:dword`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) const] Image[@(0.0.255) `&] 
[*@3 image], [@(0.0.255) double] [*@3 x1], [@(0.0.255) double] [*@3 y1], 
[@(0.0.255) double] [*@3 x2], [@(0.0.255) double] [*@3 y2], dword [*@3 flags] 
[@(0.0.255) `=] [@3 0])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,const Upp`:`:Image`&`,const Upp`:`:Xform2D`&`,Upp`:`:dword`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) const] 
Image[@(0.0.255) `&] [*@3 image], [@(0.0.255) const] Xform2D[@(0.0.255) `&] 
[*@3 transsrc], dword [*@3 flags] [@(0.0.255) `=] [@3 0])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,const Upp`:`:Image`&`,const Upp`:`:Pointf`&`,const Upp`:`:Pointf`&`,Upp`:`:dword`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) const] 
Image[@(0.0.255) `&] [*@3 image], [@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p1], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p2], dword [*@3 flags] 
[@(0.0.255) `=] [@3 0])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,const Upp`:`:Image`&`,double`,double`,double`,double`,Upp`:`:dword`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) const] 
Image[@(0.0.255) `&] [*@3 image], [@(0.0.255) double] [*@3 x1], [@(0.0.255) double] 
[*@3 y1], [@(0.0.255) double] [*@3 x2], [@(0.0.255) double] [*@3 y2], dword 
[*@3 flags] [@(0.0.255) `=] [@3 0])&]
[s2;%% Fills or strokes the path with [%-*@3 image]. The placement 
of image in the path is defined by [%-*@3 transsrc] transformation 
that maps image coordinates to current painter coordinates or 
alternatively by line segment [%-*@3 p1] [%-*@3 p2] / [%-*@3 x1] [%-*@3 y1] 
[%-*@3 x2] [%-*@3 y2] that represents top border of image. [%-*@3 flags] 
can provide FILL`_FAST flag that changes image interpolation 
to fastest n[%- earest`-neighbor method and also] provides the 
information about pixels outside image a combination of FILL`_HPAD, 
FILL`_HREPEAT, FILL`_HREFLECT, FILL`_VPAD, FILL`_VREPEAT, FILL`_VREFLECT, 
FILL`_PAD, FILL`_REPEAT, FILL`_REFLECT, where H means extension 
to left/right, V up/down, PAD means repeat border pixels, REPEAT 
means repeat image pixels, REFLECT repeat image pixels but flip 
adjacent images:&]
[s2;%% 
@@image:3327&558
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)
&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Fill`(const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 p1], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color1], [@(0.0.255) const] 
Pointf[@(0.0.255) `&] [*@3 p2], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color2], [@(0.0.255) int] [*@3 style ][@(0.0.255) `=] [* GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Fill`(double`,double`,const Upp`:`:RGBA`&`,double`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) double] [*@3 x1], [@(0.0.255) double] 
[*@3 y1], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color1], [@(0.0.255) double] 
[*@3 x2], [@(0.0.255) double] [*@3 y2], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color2], [@(0.0.255) int] [*@3 style ][@(0.0.255) `=] [* GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Fill`(const Upp`:`:RGBA`&`,const Upp`:`:RGBA`&`,const Upp`:`:Xform2D`&`,Upp`:`:dword`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color1], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) const] 
Xform2D[@(0.0.255) `&] [*@3 transsrc], dword [*@3 flags] [@(0.0.255) `=] 
[@3 0])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) const] 
Pointf[@(0.0.255) `&] [*@3 p1], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color1], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p2], [@(0.0.255) const] 
RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) int] [*@3 style ][@(0.0.255) `=] 
[* GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,double`,double`,const Upp`:`:RGBA`&`,double`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) double] 
[*@3 x1], [@(0.0.255) double] [*@3 y1], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color1], [@(0.0.255) double] [*@3 x2], [@(0.0.255) double] [*@3 y2], 
[@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) int] 
[*@3 style ][@(0.0.255) `=] [* GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,const Upp`:`:RGBA`&`,const Upp`:`:RGBA`&`,const Upp`:`:Xform2D`&`,Upp`:`:dword`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) const] 
RGBA[@(0.0.255) `&] [*@3 color1], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color2], [@(0.0.255) const] Xform2D[@(0.0.255) `&] [*@3 transsrc], 
dword [*@3 flags] [@(0.0.255) `=] [@3 0])&]
[s2;%% Fills or strokes path with linear gradient. Gradient is specified 
by two points ([%-*@3 p1] / [%-*@3 x1] [%-*@3 y1], [%-*@3 p2] / [%-*@3 x2] 
[%-*@3 y2]) and two colors [%-*@3 color1] [%-*@3 color2]. Additional 
colors to be used in between can be specified with [* ColorStop] 
method. [%-*@3 style] specifies the color of gradient outside of 
area, with options GRADIENT`_PAD, GRADIENT`_REPEAT, GRADIENT`_REFLECT 
(with meaning similar to image filling options). Variant with 
[%-*@3 transsrc] specifies mapping using transformation matrix, 
with source gradient being line `[0,0`]`-`[1,0`].&]
[s3;%% &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Fill`(const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,const Upp`:`:Pointf`&`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 f], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color1], [@(0.0.255) const] 
Pointf[@(0.0.255) `&] [*@3 c], [@(0.0.255) double] [*@3 r], [@(0.0.255) const] 
RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) int] style [@(0.0.255) `=] 
[*@3 GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Fill`(double`,double`,const Upp`:`:RGBA`&`,double`,double`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) double] [*@3 fx], [@(0.0.255) double] 
[*@3 fy], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color1], [@(0.0.255) double] 
[*@3 cx], [@(0.0.255) double] [*@3 cy], [@(0.0.255) double] [*@3 r], [@(0.0.255) const] 
RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) int] style [@(0.0.255) `=] 
[*@3 GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Fill`(const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 c], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color1], [@(0.0.255) double] 
[*@3 r], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) int] 
style [@(0.0.255) `=] [*@3 GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Fill`(double`,double`,const Upp`:`:RGBA`&`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] 
[*@3 y], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color1], [@(0.0.255) double] 
[*@3 r], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) int] 
style [@(0.0.255) `=] [*@3 GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Fill`(const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,const Upp`:`:RGBA`&`,const Upp`:`:Xform2D`&`,int`): P
ainter[@(0.0.255) `&] [* Fill]([@(0.0.255) const] Pointf[@(0.0.255) `&] 
[*@3 f], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color1], [@(0.0.255) const] 
RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) const] Xform2D[@(0.0.255) `&] 
[*@3 transsrc], [@(0.0.255) int] style [@(0.0.255) `=] [*@3 GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,const Upp`:`:Pointf`&`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) const] 
Pointf[@(0.0.255) `&] [*@3 f], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color1], [@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 c], [@(0.0.255) double] 
[*@3 r], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) int] 
style [@(0.0.255) `=] [*@3 GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,double`,double`,const Upp`:`:RGBA`&`,double`,double`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) double] 
[*@3 fx], [@(0.0.255) double] [*@3 fy], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color1], [@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y], 
[@(0.0.255) double] [*@3 r], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color2], 
[@(0.0.255) int] style [@(0.0.255) `=] [*@3 GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) const] 
Pointf[@(0.0.255) `&] [*@3 c], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color1], [@(0.0.255) double] [*@3 r], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color2], [@(0.0.255) int] style [@(0.0.255) `=] [*@3 GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,double`,double`,const Upp`:`:RGBA`&`,double`,const Upp`:`:RGBA`&`,int`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) double] 
[*@3 x], [@(0.0.255) double] [*@3 y], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color1], [@(0.0.255) double] [*@3 r], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color2], [@(0.0.255) int] style [@(0.0.255) `=] [*@3 GRADIENT`_PAD])&]
[s5;:Upp`:`:Painter`:`:Stroke`(double`,const Upp`:`:Pointf`&`,const Upp`:`:RGBA`&`,const Upp`:`:RGBA`&`,const Upp`:`:Xform2D`&`,int`): P
ainter[@(0.0.255) `&] [* Stroke]([@(0.0.255) double] [*@3 width], [@(0.0.255) const] 
Pointf[@(0.0.255) `&] [*@3 f], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color1], [@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color2], [@(0.0.255) const] 
Xform2D[@(0.0.255) `&] [*@3 transsrc], [@(0.0.255) int] style [@(0.0.255) `=] 
[*@3 GRADIENT`_PAD])&]
[s2;%% Fills or strokes path with radial gradient. Gradient start 
at focus point [%-*@3 f] / [%-*@3 fx] [%-*@3 fy] with [%-*@3 color1] 
and ends at circle with center point [%-*@3 c] / [%-*@3 x] [%-*@3 y] 
and radius [%-*@3 r] with [%-*@3 color2]. If focus point is not present, 
it is the same as the center of circle. [%-*@3 style] specifies 
the color of gradient outside of area, with options GRADIENT`_PAD, 
GRADIENT`_REPEAT, GRADIENT`_REFLECT (with meaning similar to 
image filling options). Variant with [%-*@3 transsrc] specifies 
mapping using transformation matrix, with source gradient being 
circle with center at `[0,0`] and radius 1.&]
[s3;%% &]
[s0; &]
[ {{10000F(128)G(128)@1 [s0;%% [* Painter context and attributes]]}}&]
[s9;%% Painter has notion of two types of context: normal and path 
specific. Any context changes that are done without any path 
operations performed after latest path realization operation 
(Fill, Stroke, Clip) are global `- valid until the context is 
restored to previous state with End (or painting ends). Context 
changes that are done after path was created are path specific 
`- valid only for given path.&]
[s9;%% &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Begin`(`): [@(0.0.255) void] [* Begin]()&]
[s2;%% Stores current context on the stack. This includes clipping 
regions and alpha masking.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:End`(`): [@(0.0.255) void] [* End]()&]
[s2;%% Pops and restores the context from the stack, unless the corresponding 
Begin was actually BeginMask.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:ColorStop`(double`,const Upp`:`:RGBA`&`): Painter[@(0.0.255) `&] 
[* ColorStop]([@(0.0.255) double] [*@3 pos], [@(0.0.255) const] RGBA[@(0.0.255) `&] 
[*@3 color])&]
[s2;%% Adds additional gradient [%-*@3 color] at relative position 
[%-*@3 pos]. Position is fraction of distance between gradient 
starting and ending point as defined in Fill or Stroke.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:ClearStops`(`): Painter[@(0.0.255) `&] [* ClearStops]()&]
[s2;%% Removes all positions defined by ColorStop. As ColorStop is 
usually used as path specific attribute, this is really needed 
nor used.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Opacity`(double`): Painter[@(0.0.255) `&] [* Opacity]([@(0.0.255) do
uble] [*@3 o])&]
[s2;%% Sets painting opacity to [%-*@3 o], where 1 is fully opaque 
and 0 is fully transparent.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:LineCap`(int`): Painter[@(0.0.255) `&] [* LineCap]([@(0.0.255) int] 
[*@3 linecap])&]
[s2;%% Sets line caps. [%-*@3 linecap] can be one of LINECAP`_BUTT, 
LINECAP`_SQUARE or LINECAP`_ROUND (LINECAP`_BUTT is default value):&]
[s2;%% 
@@image:2721&406
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)
&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:LineJoin`(int`): Painter[@(0.0.255) `&] [* LineJoin]([@(0.0.255) int
] [*@3 linejoin])&]
[s2;%% Sets the line joining mode. [%-*@3 linejoin] can be one of LINEJOIN`_MITER, 
LINEJOIN`_ROUND, LINEJOIN`_BEVEL (LINEJOIN`_MITER is default 
value):&]
[s2;%% 
@@image:2684&809
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&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:MiterLimit`(double`): Painter[@(0.0.255) `&] 
[* MiterLimit]([@(0.0.255) double] [*@3 l])&]
[s2; Defines a limit on the ratio of the miter length to the stroke 
width. Default value is 4. Past this maximum value, join reverts 
to bevel:&]
[s2; 
@@image:2537&887
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)
&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Dash`(const Vector`&`,double`): Painter[@(0.0.255) `&] 
[* Dash]([@(0.0.255) const] Vector<[@(0.0.255) double]>[@(0.0.255) `&] 
[*@3 dash], [@(0.0.255) double] [*@3 start])&]
[s5;:Upp`:`:Painter`:`:Dash`(const char`*`,double`): Painter[@(0.0.255) `&] 
[* Dash]([@(0.0.255) const] [@(0.0.255) char] [@(0.0.255) `*][*@3 dash], 
[@(0.0.255) double] [*@3 start] [@(0.0.255) `=] [@3 0])&]
[s2; [%% Defines ]the pattern of dashes and gaps used to stroke the 
path[%% . First value is the length of dash. If total number of 
values is odd, meaning of individual values alternates between 
dash and gap. For ][@(0.0.255) const] [@(0.0.255) char] [@(0.0.255) `*][*@3 dash][%% , 
values are defined by space separate list of numbers. ][*@3 start] 
can offset the starting position.&]
[s2;%% 
@@image:2984&421
(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)
&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:EvenOdd`(bool`): Painter[@(0.0.255) `&] [* EvenOdd]([@(0.0.255) bool
] [*@3 evenodd] [@(0.0.255) `=] [@(0.0.255) true])&]
[s2;%% Sets the filling mode to either even`-odd rule or zero`-winding 
rule.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Invert`(bool`): Painter[@(0.0.255) `&] [* Invert]([@(0.0.255) bool] 
[*@3 b] [@(0.0.255) `=] [@(0.0.255) true])&]
[s2;%% Special mode where instead of filling with color or source 
spans, affected pixels have the color channels inverted (with 
binary NOT operation). This is occasionally useful for displaying 
cursors.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:ImageFilter`(int`): Painter[@(0.0.255) `&] [* ImageFilter]([@(0.0.255) i
nt] [*@3 filter])&]
[s2;%% Sets the convolution [%-*@3 filter] used to rescale images. 
Can be one of FILTER`_NEAREST, FILTER`_BILINEAR, FILTER`_BSPLINE, 
FILTER`_COSTELLA, FILTER`_BICUBIC`_MITCHELL,&]
[s2;%% FILTER`_BICUBIC`_CATMULLROM, FILTER`_LANCZOS3.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Transform`(const Upp`:`:Xform2D`&`): Painter[@(0.0.255) `&] 
[* Transform]([@(0.0.255) const] Xform2D[@(0.0.255) `&] [*@3 m])&]
[s2;%% Multiplies transformation matrix by [%-*@3 m]. Cannot be used 
as path specific attribute change.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Translate`(double`,double`): Painter[@(0.0.255) `&] 
[* Translate]([@(0.0.255) double] [*@3 x], [@(0.0.255) double] [*@3 y])&]
[s5;:Upp`:`:Painter`:`:Translate`(const Upp`:`:Pointf`&`): Painter[@(0.0.255) `&] 
[* Translate]([@(0.0.255) const] Pointf[@(0.0.255) `&] [*@3 p])&]
[s2;%% Translates transformation matrix by [%-*@3 p] / [%-*@3 x] [%-*@3 y]. 
Cannot be used as path specific attribute change.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Rotate`(double`): Painter[@(0.0.255) `&] [* Rotate]([@(0.0.255) doub
le] [*@3 a])&]
[s2;%% Rotates transformation matrix by [%-*@3 a] radians. Cannot be 
used as path specific attribute change.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Scale`(double`,double`): Painter[@(0.0.255) `&] 
[* Scale]([@(0.0.255) double] [*@3 scalex], [@(0.0.255) double] [*@3 scaley])&]
[s2;%% Scales the transformation by [%-*@3 scalex], [%-*@3 scaley] factors. 
Cannot be used as path specific attribute change.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Scale`(double`): Painter[@(0.0.255) `&] [* Scale]([@(0.0.255) double
] [*@3 scale])&]
[s2;%% Same as Scale( [%-*@3 scale], [%-*@3 scale]).&]
[s3; &]
[s0; &]
[ {{10000F(128)G(128)@1 [s0;%% [* Other operations]]}}&]
[s4;H0; &]
[s5;:Upp`:`:Painter`:`:Clear`(const Upp`:`:RGBA`&`): [@(0.0.255) void] 
[* Clear]([@(0.0.255) const] RGBA[@(0.0.255) `&] [*@3 color ][@(0.0.255) `=] 
RGBAZero())&]
[s2;%% Sets all values in the target canvas to color. This is usually 
the first operation performed. Default RGBAZero() values sets 
canvas to be initially completely transparent.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Paint`(const Upp`:`:Painting`&`): [@(0.0.255) void] 
[* Paint]([@(0.0.255) const] Painting[@(0.0.255) `&] [*@3 p])&]
[s2;%% Replays all painting commands contained Painting object (which 
can be created using PaintingPainter class)&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:Clip`(`): Painter[@(0.0.255) `&] [* Clip]()&]
[s2;%% Converts current path into clipping region and combines it 
with existing clipping region. This new clipping region is then 
valid until next End command. .&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:BeginOnPath`(double`,bool`): [@(0.0.255) void] 
[* BeginOnPath]([@(0.0.255) double] [*@3 q], [@(0.0.255) bool] [*@3 absolute] 
[@(0.0.255) `=] [@(0.0.255) false])&]
[s2;%% Does takes current path, does Begin operation, then sets the 
current transformation so that it lies on current path at length 
[%-*@3 q] (if [%-*@3 absolute][%-  ]is true, it is length of path, 
ratio of length of path otherwise (0 is the start of path, 1 
end of path) and is rotated in the direction of the path. The 
path is extrapolated on either side by line with the last path 
direction to cover positions outside the path. This transformation 
is valid till the End command.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:BeginMask`(`): [@(0.0.255) void] [* BeginMask]()&]
[s2;%% Starts alpha mask definition. Anything drawn since BeginMask 
till End command is not really drawn to the canvas and only alpha 
value are stored as mask that is, after the End command, combined 
with current alpha mask and used for alpha masking.&]
[s3; &]
[s4; &]
[s5;:Upp`:`:Painter`:`:EndPath`(`): [@(0.0.255) void] [* EndPath]()&]
[s2;%% Simply cancels the last path without drawing anything. This 
is occasionally useful with complex drawing code.&]
[s3;%% &]
[s3;%% &]
[s3;%% &]
[s0; &]
[ {{10000@(113.42.0) [s0;%% [*@7;4 NilPainter]]}}&]
[s0;%% &]
[s1;:Upp`:`:NilPainter: [*3 NilPainter][3  ][@(0.0.255)3 :][3  ][@(0.0.255)3 public][3  
Painter]&]
[s2;%% NilPainter is special variant of Painter that simply ignores 
all invoked operation. It is useful in more complex code where 
e.g. the same routine is first used with NilPainter for calculating 
dimension of display output and then in second pass for actual 
painting.]]